Create app.py

app.py

@@ -0,0 +1,88 @@
+import streamlit as st
+import numpy as np
+import pickle
+import streamlit.components.v1 as components
+from sklearn.feature_extraction.text import CountVectorizer
+from sklearn.model_selection import train_test_split
+import pandas as pd
+# Separate target and feature column in X and y variable
+df = pd.read_csv('stress.csv')
+# X will be the features
+X = np.array(df["text"])
+
+# y will be the target variable
+y = np.array(df["label"])
+cv = CountVectorizer()
+# Load the pickled model
+
+X = cv.fit_transform(X)
+X_train, X_test, y_train, y_test = train_test_split(X, y,
+                                                test_size=0.33,
+                                                random_state=42)
+
+# Function for model prediction
+def model_prediction(features):
+    features = cv.transform([features]).toarray()
+    pickled_model = pickle.load(open('Stress_Detection_BernoulliNB.pkl', 'rb'))
+    Message = str(list(pickled_model.predict(features)))
+
+    return Message
+
+def app_design():
+    # Add input fields for High, Open, and Low values
+    image = '36.png' # Load image 
+    st.image(image, use_column_width=True)
+    
+    st.subheader("Enter the following values:")
+
+    text= st.text_input("Enter your message")
+    # Create a feature list from the user inputs
+    features = text # add features according to notebook
+    
+    # Make a prediction when the user clicks the "Predict" button
+    if st.button('Predict Sarcasm'):  
+        predicted_value = model_prediction(features)
+        if predicted_value == "['Stress']":
+            st.success("Your message contains Stress") 
+        elif predicted_value ==  "['No Stress']":
+              st.success("Your message doesnot contains Stress")       
+                 
+
+
+def about_hidevs():
+
+        components.html("""
+        <div>
+        <h4>🚀 Unlock Your Dream Job with HiDevs Community!</h4>
+        <p class="subtitle">🔍 Seeking the perfect job? HiDevs Community is your gateway to career success in the tech industry. Explore free expert courses, job-seeking support, and career transformation tips.</p>
+        <p class="subtitle">💼 We offer an upskill program in <b>Gen AI, Data Science, Machine Learning</b>, and assist startups in adopting <b>Gen AI</b> at minimal development costs.</p>
+        <p class="subtitle">🆓 Best of all, everything we offer is <b>completely free</b>! We are dedicated to helping society.</p>
+        <p class="subtitle">Book free of cost 1:1 mentorship on any topic of your choice — <a class="link" href="https://topmate.io/deepakchawla1307">topmate</a></p>
+        <p class="subtitle">✨ We dedicate over 30 minutes to each applicant’s resume, LinkedIn profile, mock interview, and upskill program. If you’d like our guidance, check out our services <a class="link" href="https://hidevscommunity.wixsite.com/hidevs">here</a></p>
+        <p class="subtitle">💡 Join us now, and turbocharge your career!</p>
+        <p class="subtitle"><a class="link" href="https://hidevscommunity.wixsite.com/hidevs" target="__blank">Website</a>
+        <a class="link" href="https://www.youtube.com/@HidevsCommunity1307/" target="__blank">YouTube</a>
+        <a class="link" href="https://www.instagram.com/hidevs_community/" target="__blank">Instagram</a>
+        <a class="link" href="https://medium.com/@hidevscommunity" target="__blank">Medium</a>
+        <a class="link" href="https://www.linkedin.com/company/hidevs-community/" target="__blank">LinkedIn</a>
+        <a class="link" href="https://github.com/hidevscommunity" target="__blank">GitHub</a></p>
+      </div>
+        """,
+                    height=600)
+
+def main():
+
+        # Set the app title and add your website name and logo
+        st.set_page_config(
+        page_title="Stress Detection",
+        page_icon=":chart_with_upwards_trend:",
+        )
+    
+        st.title("Welcome to our Stress Detection App!")
+    
+        app_design()    
+        st.header("About HiDevs Community")
+        about_hidevs()
+
+if __name__ == '__main__':
+        main()